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Temperature-related biodiversity change across temperate marine and terrestrial systems

Abstract

Climate change is reshaping global biodiversity as species respond to changing temperatures. However, the net effects of climate-driven species redistribution on local assemblage diversity remain unknown. Here, we relate trends in species richness and abundance from 21,500 terrestrial and marine assemblage time series across temperate regions (23.5–60.0° latitude) to changes in air or sea surface temperature. We find a strong coupling between biodiversity and temperature changes in the marine realm, where species richness mostly increases with warming. However, biodiversity responses are conditional on the baseline climate, such that in initially warmer locations richness increase is more pronounced while abundance declines with warming. In contrast, we do not detect systematic temperature-related richness or abundance trends on land, despite a greater magnitude of warming. As the world is committed to further warming, substantial challenges remain in maintaining local biodiversity amongst the non-uniform inflow and outflow of ‘climate migrants’. Temperature-driven community restructuring is especially evident in the ocean, whereas climatic debt may be accumulating on land.

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Fig. 1: Conceptual figure of the mechanisms underlying our hypotheses for how temperature-related biodiversity change may unfold unevenly across the planet.
Fig. 2: Variation in temperature and local biodiversity trends across the time series.
Fig. 3: Biodiversity responses to temperature change and its interaction with baseline climate.
Fig. 4: Biodiversity responses to the combined effect of temperature change and baseline climate.

Data availability

All the data can be accessed through either the BioTIME database on Zenodo (https://doi.org/10.5281/zenodo.1211105) or the BioTIME website (http://biotime.st-andrews.ac.uk/).

Code availability

Code to reproduce the analysis is available on GitHub (https://github.com/lauraantao/Temp_Biodiv_Change) and in an online archive at Zenodo59.

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Acknowledgements

We are grateful to all the scientists, data collectors and their funders for making data publicly available. We thank the University of St Andrews Bioinformatics Unit (Wellcome Trust ISSF grant no. 105621/Z/14/Z). L.H.A. acknowledges funding from PBL Netherlands Environmental Assessment Agency as part of the GLOBIO project (www.globio.info), and from the Jane and Aatos Erkko foundation. A.E.B. was supported by the Canada Research Chairs Programme. S.A.B. acknowledges the support of the German Centre of Integrative Biodiversity Research (iDiv) Halle–Jena–Leipzig (funded by the German Research Foundation; no. FZT 118). C.W. was supported by the Natural Environmental Research Council (grant no. 563 NE/L002531/1). M.D. is funded by a Leverhulme Fellowship and by the John Templeton Foundation (grant no. 60501, ‘Putting the Extended Evolutionary Synthesis to the Test’). The BioTIME database was created using funding from the European Research Council (AdG BioTIME (no. 250198) and PoC BioCHANGE (no. 727440)) granted to A.E.M., and we also acknowledge funding from the Leverhulme Centre for Anthropocene Biodiversity. We thank G. Daskalova for valuable input on an early draft of the manuscript and suggestions for the figures. The two icons in the figures are from the Noun Project under CCBY licence: land by A. Skowalsky, and wave by B. Farias.

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Contributions

M.D. and A.M.S. conceived the idea, and all authors contributed to the design of the project. L.H.A. analysed the data in close consultation with S.A.B., A.E.B., M.D. and A.M.S. L.H.A. wrote the first draft of the manuscript. L.H.A., A.E.B., M.D., A.M.S., S.A.B., C.W., S.R.S. and A.E.M. all contributed to manuscript completion and revision.

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Correspondence to Laura H. Antão or Amanda E. Bates.

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Extended data

Extended Data Fig. 1 Location of temperate biodiversity time series for each realm.

Dots are coloured according to the temperature change experienced during the period of biodiversity monitoring in those locations (a), and with the corresponding rates of species richness change (b). Credit: b farias, CL (wave image) and Alexander Skowalsky, HU (tree image), The Noun Project (https://thenounproject.com/); world maps produced using the R package tidyverse v.1.2.1 (ref. 61).

Extended Data Fig. 2 Variation among time series regarding temporal sampling.

(a) the starting year (binned into 2-year periods); (b) the number of years sampled; (c) the duration (time period between first and last sample) of the time series; and (d) duration of time series as a function of the number of samples, where colours represent the number of time series for a given combination of duration and number of samples.

Extended Data Fig. 3 Marginal effects of the interaction between temperature change (°C per year) and baseline climate on the biodiversity responses (rate per year).

The coloured fitted lines indicate three long-term annual mean temperature values representing the range across the time series (specifically the mean ± one standard deviation for each realm), and the shaded areas represent the 95% credible interval estimated from the meta-analytical models. For each biodiversity metric, the top row is for marine locations, and the bottom row for terrestrial locations (note the different scales among metrics). Credit: b farias, CL (wave image) and Alexander Skowalsky, HU (tree image), The Noun Project (https://thenounproject.com/).

Extended Data Fig. 4 Comparison of the meta-analytical model estimates using different variables for the baseline climate, as well as latitude.

Dots represent the estimated parameters and whiskers indicate the 95% credible intervals from the Bayesian meta-analysis. Overall, our results were robust to the different temperature variables used: long-term annual mean (Mean_Temp) and maximum temperature (Max_Temp) from the databases WorldClim and Bio-ORACLE, and average air and sea surface temperature in the first year sampled from the HadCRUT4 database (Year1_Temp). Additionally, latitude did not show interacting effects with temperature change.

Extended Data Fig. 5 Sensitivity analysis for each biodiversity metric.

The grey points show the estimated coefficients (and their 95% credible intervals) from 100 meta-analytical models fit to subsets of the marine data, which were randomly subsampled to match the number of locations and latitudinal range of the terrestrial data. Despite the increase in uncertainty due to the smaller data subsets (that is larger credible intervals), comparing the parameter estimates based on the random sub-samples with the parameters estimated using the entire data (blue dots) shows that the marine estimates were not biased due to uneven sampling. Text insets indicate the parameter estimates for the full marine data (blue) and the average across the 100 random sub-samples (grey).

Extended Data Fig. 6 Variation in biodiversity estimated slopes.

Variation in biodiversity estimated slopes as a function of (a) the number of years sampled used to calculate the trends in each time series, where the size of the points represents the duration of the time series (that is Yearend – Yearstart + 1); (b) the duration of the time series; and (c) the start year of each time series, where the size of the points represents the number of years sampled. In all the plots, colours indicate whether estimated slopes were significantly positive (blue), negative (red) or neutral (that is not statistically different to zero; grey).

Extended Data Fig. 7 Variation in biodiversity estimated standard errors.

Variation in biodiversity estimated standard errors as a function of (a) the number of years sampled used to calculate the trends in each time series, where the size of the points represents the duration of the time series (that is Yearend – Yearstart + 1); (b) the duration of the time series; and (c) the start year of each time series, where the size of the points represents the number of years sampled. In all the plots, colours indicate whether estimated slopes were significantly positive (blue), negative (red) or neutral (that is not statistically different to zero; grey).

Extended Data Fig. 8 Density plots of the posterior distributions of the estimated random slopes for the temperature change effect per taxonomic group in the marine realm.

The black vertical line indicates the overall slope estimate for each biodiversity response, with the corresponding 95% credible interval as grey shading; vertical dotted lines indicate zero. The numbers in brackets indicate the number of time series for each taxonomic group (see Supplementary Tables 36 for complete model outputs). In two instances, these distributions showed some tendency for deviating from the overall estimated mean. Specifically, “Birds” showed more negative trends for richness change than the average across taxa, and “Multiple taxa” showed more positive trends for abundance change than the average estimate. Yet, both distributions showed extensive overlap with the other taxonomic groups, as well as with the confidence intervals for the overall mean responses. Thus, we refrain from reading too much into these patterns, given the biases in the BioTIME data, and rather focus on the general patterns of change. Credit: b farias, CL (wave image), The Noun Project (https://thenounproject.com/).

Extended Data Fig. 9 Density plots of the posterior distributions of the estimated random slopes for the temperature change effect per taxonomic group in the terrestrial realm.

The black vertical line indicates the overall slope estimate for each biodiversity response, with the corresponding 95% credible interval as grey shading; vertical dotted lines indicate zero. The numbers in brackets indicate the number of time series for each taxonomic group (see Supplementary Tables 36 for complete model outputs). Credit: Alexander Skowalsky, HU (tree image), The Noun Project (https://thenounproject.com/).

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Antão, L.H., Bates, A.E., Blowes, S.A. et al. Temperature-related biodiversity change across temperate marine and terrestrial systems. Nat Ecol Evol 4, 927–933 (2020). https://doi.org/10.1038/s41559-020-1185-7

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